Thousands of genes have been well demonstrated to play important roles in cancer progression. As genes do not function in isolation, they can be grouped into “networks” based on their interactions. In this study, we discover a network regulating Claudin-4 in gastric cancer. We observe that Claudin-4 is up-regulated in gastric cancer and is associated with poor prognosis. Claudin-4 reinforce proliferation, invasion, and EMT in AGS, HGC-27, and SGC-7901 cells, which could be reversed by miR-596 and miR-3620-3p. In addition, lncRNA-KRTAP5-AS1 and lncRNA-TUBB2A could act as competing endogenous RNAs to affect the function of Claudin-4. Our results suggest that non-coding RNAs play important roles in the regulatory network of Claudin-4. As such, non-coding RNAs should be considered as potential biomarkers and therapeutic targets against gastric cancer.

Identification of intrinsic disorder in proteins relies in large part on computational predictors, which demands that their accuracy should be high. Since intrinsic disorder carries out a broad range of cellular functions, it is desirable to couple the disorder and disorder function predictions. We report a computational tool, flDPnn, that provides accurate, fast and comprehensive disorder and disorder function predictions from protein sequences. The recent Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment and results on other test datasets demonstrate that flDPnn offers accurate predictions of disorder, fully disordered proteins and four common disorder functions. These predictions are substantially better than the results of the existing disorder predictors and methods that predict functions of disorder. Ablation tests reveal that the high predictive performance stems from innovative ways used in flDPnn to derive sequence profiles and encode inputs. flDPnn’s webserver is available at http://biomine.cs.vcu.edu/servers/flDPnn/

Artificial scent screening systems (known as electronic noses, E‐noses) have been researched extensively. A portable, automatic, and accurate, real‐time E‐nose requires both robust cross‐reactive sensing and fingerprint pattern recognition. Few E‐noses have been commercialized because they suffer from either sensing or pattern‐recognition issues. Here, cross‐reactive colorimetric barcode combinatorics and deep convolutional neural networks (DCNNs) are combined to form a system for monitoring meat freshness that concurrently provides scent fingerprint and fingerprint recognition. The barcodes—comprising 20 different types of porous nanocomposites of chitosan, dye, and cellulose acetate—form scent fingerprints that are identifiable by DCNN. A fully supervised DCNN trained using 3475 labeled barcode images predicts meat freshness with an overall accuracy of 98.5%. Incorporating DCNN into a smartphone application forms a simple platform for rapid barcode scanning and identification of food freshness in real time. The system is fast, accurate, and non‐destructive, enabling consumers and all stakeholders in the food supply chain to monitor food freshness.

Background: Metformin has been reported to possess anti-cancer properties in addition to glucose-lowering activity and numerous systematic reviews and meta-analyses have studied the association between metformin use and cancer incidence or survival outcomes. We performed an umbrella review to assess the robustness of these associations to facilitate proper interpretation of these results to inform clinical and policy decisions.Methods: We searched PubMed and Embase systematic reviews and meta-analyses investigating the effect of metformin use on cancer incidence or survival outcomes published from inception to September 2, 2018. We estimated the summary effect size, the 95% CI, and the 95% prediction interval, heterogeneity, evidence of small-study effects, and evidence of excess significance bias.Results: We included 21 systematic reviews and meta-analyses covering 11 major anatomical sites and 33 associations. There was strong evidence for the association between metformin use and decreased pancreatic cancer incidence. The association between metformin use and improved colorectal cancer overall survival (OS) was supported by highly suggestive evidence. Seven associations (all cancer incidence, all cancer OS, breast cancer OS, colorectal cancer incidence, liver cancer incidence, lung cancer OS, and pancreatic cancer OS) presented only suggestive evidence. The remaining 24 associations were supported by weak or not-suggestive evidence.Conclusions: Associations between metformin use and pancreatic cancer incidence or colorectal cancer OS are supported by strong or highly suggestive evidence, respectively. However, these results should be interpreted with caution due to the poor methodological quality of the systematic reviews and meta-analyses.

Some of the intrinsically disordered proteins and protein regions are promiscuous interactors that are involved in one-to-many and many-to-one binding. Several studies have analyzed enrichment of intrinsic disorder among the promiscuous hub proteins. We extended these works by providing a detailed functional characterization of the disorder-enriched hub protein-protein interactions (PPIs), including both hubs and their interactors, and by analyzing their enrichment among disease-associated proteins. We focused on the human interactome, given its high degree of completeness and relevance to the analysis of the disease-linked proteins. We quantified and investigated numerous functional and structural characteristics of the disorder-enriched hub PPIs, including protein binding, structural stability, evolutionary conservation, several categories of functional sites, and presence of over twenty types of posttranslational modifications (PTMs). We showed that the disorder-enriched hub PPIs have a significantly enlarged number of disordered protein binding regions and long intrinsically disordered regions. They also include high numbers of targeting, catalytic, and many types of PTM sites. We empirically demonstrated that these hub PPIs are significantly enriched among 11 out of 18 considered classes of human diseases that are associated with at least 100 human proteins. Finally, we also illustrated how over a dozen specific human hubs utilize intrinsic disorder for their promiscuous PPIs.

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Breast cancer (BC) is the most common malignant tumor among women, with high morbidity and mortality. Its onset, development, metastasis, and prognosis vary among individuals due to the interactions between tumors and host immunity. Many diverse mechanisms have been associated with BC, with immune evasion being the most widely studied to date. Tumor cells can escape from the body’s immune response, which targets abnormal components and foreign bodies, using different approaches including modification of surface antigens and modulation of the surrounding environment. In this review, we summarize the mechanisms and factors that impact the immunoediting process and analyze their functions in detail.

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